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目前提供的镜像ubuntu-gpu-mxnet1.3、ubuntu-gpu-tf1.12，似乎有一些问题，尝试修复了一下 #118

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Feb 3, 2019
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目前提供的镜像ubuntu-gpu-mxnet1.3、ubuntu-gpu-tf1.12，似乎有一些问题，尝试修复了一下 #118

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49 changes: 49 additions & 0 deletions xdl/docker/Dockerfile_for_gpu
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# Use one of the GPU based XDL images as the parent image
FROM registry.cn-hangzhou.aliyuncs.com/xdl/xdl:ubuntu-gpu-mxnet1.3
#FROM registry.cn-hangzhou.aliyuncs.com/xdl/xdl:ubuntu-gpu-tf1.12

LABEL maintainer "icemoon1987 <[email protected]>"

# Remove CUDA and Nvidia related packages from the parent image to avoid conflict with the host Nvidia driver's libraries and tools.
RUN apt -y remove cuda-*
RUN apt -y remove nvidia-*

# Install CUDA computing and machine learning components. Refer to the official Nvidia Dockerfile: https://gitlab.com/nvidia/cuda/blob/ubuntu16.04/9.0/base/Dockerfile
RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates apt-transport-https gnupg-curl && \
rm -rf /var/lib/apt/lists/* && \
NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
NVIDIA_GPGKEY_FPR=ae09fe4bbd223a84b2ccfce3f60f4b3d7fa2af80 && \
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub && \
apt-key adv --export --no-emit-version -a $NVIDIA_GPGKEY_FPR | tail -n +5 > cudasign.pub && \
echo "$NVIDIA_GPGKEY_SUM cudasign.pub" | sha256sum -c --strict - && rm cudasign.pub && \
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/cuda.list && \
echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list

ENV CUDA_VERSION 9.0.176

ENV CUDA_PKG_VERSION 9-0=$CUDA_VERSION-1
RUN apt-get update && apt-get install -y --no-install-recommends \
cuda-cudart-$CUDA_PKG_VERSION cuda-cublas-$CUDA_PKG_VERSION cuda-core-$CUDA_PKG_VERSION cuda-cufft-$CUDA_PKG_VERSION cuda-curand-$CUDA_PKG_VERSION cuda-cusolver-$CUDA_PKG_VERSION cuda-cusparse-$CUDA_PKG_VERSION cuda-libraries-$CUDA_PKG_VERSION libcudnn7=7.0.5.15-1+cuda9.0 libcudnn7-dev=7.0.5.15-1+cuda9.0 libnccl2=2.1.4-1+cuda9.0 libnccl-dev=2.1.4-1+cuda9.0 && \
ln -s cuda-9.0 /usr/local/cuda && \
rm -rf /var/lib/apt/lists/*

# nvidia-docker 1.0
LABEL com.nvidia.volumes.needed="nvidia_driver"
LABEL com.nvidia.cuda.version="${CUDA_VERSION}"

RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf

ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64

# nvidia-container-runtime
# Add these environment variables, so nvidia-docker will map the driver libraries and tools from the host to the container.
# Refer to: https://devblogs.nvidia.com/gpu-containers-runtime
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
ENV NVIDIA_REQUIRE_CUDA "cuda>=9.0"

# Fix the bug of pip
RUN sed -i 's/pip._internal/pip/g' /usr/local/bin/pip